Controlling dynamical systems in uncertain environments is a fundamental and essential problem in several fields, ranging from robotics, to healthcare, to management, to science, to economics and to finance. Given a system with dynamics described, for example, by a controlled diffusion process, a stochastic optimal control problem is to find an optimal feedback policy to optimize an objective function. Risk management has always been an important part of stochastic optimal control problems to guarantee or optimize the likelihood of safety during the execution of control policies. For instance, in self-driving car applications, it is desirable that autonomous cars depart from origins to reach destinations with minimum energy and at the same time maintain bounded probability of collision. Ensuring such performance is critical before deploying autonomous cars in real life.